In current clinical practice, fear of movement has been considered a significant factor affecting patient disability and needs to be evaluated and addressed to accomplish successful rehabilitation strategies. Therefore, the study aims (1) to establish the association between kinesiophobia and knee pain intensity, joint position sense (JPS), and functional performance, and (2) to determine whether kinesiophobia predicts pain intensity, JPS, and functional performance among individuals with bilateral knee osteoarthritis (KOA). This cross-sectional study included 50 participants (mean age: 67.10 ± 4.36 years) with KOA. Outcome measures: The level of kinesiophobia was assessed using the Tampa Scale of Kinesiophobia, pain intensity using a visual analog scale (VAS), knee JPS using a digital inclinometer, and functional performance using five times sit-to-stand test. Knee JPS was assessed in target angles of 15°, 30°, and 60°. Pearson’s correlation coefficients and simple linear regressions were used to analyze the data. Significant moderate positive correlations were observed between kinesiophobia and pain intensity (r = 0.55, p < 0.001), JPS (r ranged between 0.38 to 0.5, p < 0.05), and functional performance (r = 0.49, p < 0.001). Simple linear regression analysis showed kinesiophobia significantly predicted pain intensity (B = 1.05, p < 0.001), knee JPS (B ranged between 0.96 (0° of knee flexion, right side) to 1.30 (15° of knee flexion, right side)), and functional performance (B = 0.57, p < 0.001). We can conclude that kinesiophobia is significantly correlated and predicted pain intensity, JPS, and functional performance in individuals with KOA. Kinesiophobia is a significant aspect of the recovery process and may be taken into account when planning and implementing rehabilitation programs for KOA individuals.

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Precisely assessing the severity of persons with Covid-19 at an early stage is an effective way to increase the survival rate of patients. Based on the initial screening, to identify and triage the people at highest risk of complications that can result in mortality risk in patients is a challenging problem, especially in developing nations around the world. This problem is further aggravated due to the shortage of specialists. Using machine learning (ML) techniques to predict the severity of persons with Covid-19 in the initial screening process can be an effective method which would enable patients to be sorted and treated and accordingly receive appropriate clinical management with optimum use of medical facilities. In this study, we applied and evaluated the effectiveness of three types of Artificial Neural Network (ANN), Support Vector Machine and Random forest regression using a variety of learning methods, for early prediction of severity using patient history and laboratory findings. The performance of different machine learning techniques to predict severity with clinical features shows that it can be successfully applied to precisely and quickly assess the severity of the patient and the risk of death by using patient history and laboratory findings that can be an effective method for patients to be triaged and treated accordingly.

Background Knee osteoarthritis (KOA) is a painful degenerative joint disease that may limit activities of daily living. This study aimed to determine the relationship between quadriceps endurance and knee joint position sense (JPS) in KOA individuals and compare the quadriceps endurance and knee JPS with and without KOA. Methods This comparative cross-sectional study was conducted in medical rehabilitation clinics, King Khalid University, Saudi Arabia. This study recruited 50 individuals diagnosed with unilateral KOA (mean age = 67.10 ± 4.36 years) and 50 asymptomatic individuals (mean age = 66.50 ± 3.63 years). Quadriceps isometric endurance capacity (sec) was measured using a fatigue resistance test, and knee JPS (degrees) were assessed using a digital inclinometer and evaluated in sitting and standing positions. Results Quadriceps isometric endurance showed a significant moderate negative correlation with knee JPS in 20° of flexion (r = -0.48, p < 0.001); 40° of flexion: r = -0.62, p < 0.001; 60° of flexion: r = -0.58, p < 0.001) in sitting and 20° of flexion (r = -0.25, p = 0.084) in standing position in KOA individuals. When compared to the asymptomatic, the quadriceps endurance was lower (p < 0.001), and knee joint position errors were larger (p < 0.001) in KOA individuals. Conclusion Results of this study showed that quadriceps endurance capacity is negatively associated with knee JPS. KOA individuals demonstrated lower quadriceps endurance and larger JPS compared to asymptomatic.

Objectives To determine the knowledge of falls risk factors among home healthcare (HHC) professionals and the practice patterns of HHC professionals regarding falls prevention. Methods A modified version of a survey designed and validated for use in home healthcare settings was distributed to HHC professionals for self-completion. Responses were collected and analysed using descriptive methods. Results Out of 80 surveys distributed to 23 HHC centres, 52 returned surveys were included for analyses (completed by physicians, physical therapists [PTs] and nurses). In terms of practice patterns, 82.7% of participants always asked older adults if they have a history of falls, 81% always identified falls risk factors, 73% documented risk factors for falling and 71% always provided interventions to address falls risk factors. Environmental hazards were the most common risk factor identified by HHC professionals. Approximately one quarter of nurses felt they had little knowledge of falls risk factors. Conclusion Over 70% of HHC professionals acknowledged the importance of falls, and over 80% of participants displayed knowledge of falls prevention factors. As HHC professionals most likely to encounter patients requiring intervention for falls prevention, physical therapists may benefit from training programmes to help identify important falls risk factors.